ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LAWRENCE, MA · MAY 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/lawrence/may-2022-report
Monthly Traffic Safety Analysis
117 CRASHES IN
LAWRENCE, MA
MAY 2022
In May 2022, LAWRENCE, MA recorded 117 total crashes, a decrease of 29.1% from the 165 crashes reported in May 2021. Total injuries also decreased by 38.0%, from 50 to 31. The most notable year-over-year shift was the 80% reduction in hit-and-run crashes, falling from 10 to 2.
117
▼ -29.1%was 165
Total Crash Events
0
Persons Killed
31
▼ -38.0%was 50
Persons Injured
2
▼ -80.0%was 10
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in LAWRENCE, MA shows a significant decrease year-over-year, with total crashes falling by 29.1% from 165 in May 2021 to 117 in May 2022. This decline is also reflected in a 38.0% reduction in total injuries, from 50 to 31. Fatalities remained at zero for both periods.
2
Hit-and-Run Crashes — May 2022
▼ -80.0% vs prior (10)
Hit-and-run crashes experienced a substantial decrease, falling from 10 in May 2021 to 2 in May 2022, an 80% reduction. Consequently, the hit-and-run rate decreased from 6.1% to 1.7% of all crashes. This indicates a positive trend in reducing hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
29
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Monday in May 2021, with 32 crashes, to Sunday in May 2022, which saw 27 crashes. The peak hour also changed, moving from 2 PM with 16 crashes in May 2021 to 4 PM with 12 crashes in May 2022. While overall crash counts decreased, Sunday saw a 50% increase in crashes, rising from 18 to 27.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero for both May 2021 and May 2022. There was a notable increase in serious injury crashes, rising from 1 (0.6% share) in May 2021 to 4 (3.4% share) in May 2022. Conversely, possible injury crashes decreased from 13 (7.9% share) to 4 (3.4% share) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, "Inattention" saw the largest decrease, dropping by 19 crashes from 27 in May 2021 to 8 in May 2022, a 70.4% reduction. "Disregarded traffic signs, signals, road markings" also significantly decreased by 9 crashes, from 11 to 2, an 81.8% change. "No improper driving" remained the most frequently cited factor in both periods, though its count decreased from 46 to 34 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions decreased from 107 in May 2021 to 73 in May 2022, while crashes in "Rain" conditions decreased from 14 to 7. The number of crashes on "Wet" road surfaces saw a significant reduction, falling from 29 to 9. Crashes during "Daylight" decreased from 132 to 79, while those in "Dark - lighted roadway" conditions increased from 28 to 34.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 26.5%, from 340 in May 2021 to 250 in May 2022. Honda remained the top vehicle make involved, though its count decreased from 95 to 72. All age groups saw a decrease in representation, with the 0-15 age group experiencing the largest percentage drop of 53.3%, from 30 to 14 persons.
Top Vehicle Makes (250 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
66 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (286 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones decreased by 31, from 120 in May 2021 to 89 in May 2022, a 25.8% reduction. Crashes in 20 mph speed zones decreased by 80%, from 10 to 2. However, crashes in 25 mph speed zones increased by 81.8%, rising from 11 to 20 year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2022-05-01 through 2022-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: LAWRENCE, MA
- Total crash records analyzed: 117
- Total persons involved: 349
- Total vehicles involved: 250
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "LAWRENCE, MA Crash Intelligence Report: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lawrence/may-2022-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-05-01 – 2022-05-31
Generated: June 21, 2026 · All rights reserved